Method and Apparatus For Detecting Performance, Availability and Content Deviations in Enterprise Software Applications

• US 20080244319A1
• Filed: 03/29/2005
• Published: 10/02/2008
• Est. Priority Date: 03/29/2004
• Status: Abandoned Application

• Current Assignee: Certagon Ltd.
• Original Assignee: Certagon Ltd.
• Inventors: Cohen, Yoav, Chernabroda, Yoav, Barzilai, David, Nehab, Smadar, Wolf, Ron, Entin, Gadi, Floman, Roni
• Application Number:
  US10/599,541
• Publication Number:
  US 20080244319A1
• Time in Patent Office: Days
• US Class Current: 714/38
• CPC Class Codes: G06F 11/0709 in a distributed system consisting of a plurality of standalone computer nodes, e.g. clusters, client-server systems
• CPC Class Codes: G06F 11/0715 in a system implementing multitasking multitasking per se G06F9/46
• CPC Class Codes: G06F 11/0751 Error or fault detection not based on redundancy power supply failures G06F1/30; network fault management H04L41/06
• CPC Class Codes: G06F 11/079 Root cause analysis, i.e. error or fault diagnosis in a hardware test environment G06F11/22; in a software test environment G06F11/36
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
• CPC Class Codes: G06F 11/3466 Performance evaluation by tracing or monitoring
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 11/366 using diagnostics G06F11/0703 takes precedence
• CPC Class Codes: G06F 2201/81 Threshold
• CPC Class Codes: G06F 2201/86 Event-based monitoring
• CPC Class Codes: G06F 2201/87 Monitoring of transactions
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

A system (200) comprises a plurality of data collectors (210), a correlator (220), a context analyser (230), a baseline analyser (250), a database (260), and a graphical user interface (GUI) (270). The data collectors (210) are deployed on the services or applications that they monitor, or on the network between these applications as a network appliance, and are designed to capture messages that are passed between the various services. The data collectors (210) are non-intrusive, i.e. they do not to impact the behavior of the monitored services. The data collectors (210) can capture messages transmitted using communication protocols including, but not limited to, SOAP, XML, HTTP, JMS, MSMQ, and the like.

Claims

1. An apparatus for detecting performance, availability and content deviations in enterprise software applications, comprising:

a plurality of data collectors for intercepting messages exchanged between independent services in an enterprise software application; and

an analyzer for determining a baseline for said enterprise software application and for detecting deviations from said baseline.

2. The apparatus of claim 1, further comprising:

a graphical user interface (GUI) for displaying deviations from said baseline in said enterprise software application.

3. The apparatus of claim 2, said analyzer comprising:

a collector manager for controlling said plurality of data collectors;

a correlation engine (CE) for correlating streams of said messages to a transaction;

a statistical processor for collecting real-time statistics on entities within said enterprise software application;

a baseliner for determining at least said baseline, wherein said baseline represents a normal behavior of said entities within said enterprise software application;

a fault prediction and detection engine (FPDE) for performing an early detection of deviations from said baseline in said enterprise software application; and

a presentation and alerts engine for generating reports and alerts for display on said GUI.

4. The apparatus of claim 3, said analyzer further comprising:

an analytic processor for analyzing overall activity of said transactions of said enterprise software application.

5. The apparatus of claim 3, said analyzer further comprising:

a root cause analyzer (RCA) for automatically providing a detailed analysis of a root cause of each fault detected by said FPDE.

6. The apparatus of claim 3, wherein said data collectors capture messages transmitted using communication protocols comprising any of:

a simple object access protocol (SOAP);

a hypertext transfer protocol (HTTP);

an extensible markup language (XML);

a Microsoft message queuing (MSMQ); and

a Java message service (JMS).

7. The apparatus of claim 3, said FPDE performing early detection of any of:

operation faults (bugs) in said enterprise software application; and

decrement in performance of said user enterprise software application.

8. The apparatus of claim 7, wherein operation faults are detected during production of said enterprise software application.

9. The apparatus of claim 1, said data collectors receiving said messages through an application programming interface (API).

10. The apparatus of claim 1, wherein said baseline is determined based on any:

content of said messages;

context of said messages; and

real-time statistics.

11. The apparatus of claim 10, wherein said real-time statistics comprise any of:

throughput measurements; and

average response time measurements of business transactions.

12. A method for detecting performance, availability and content deviations in enterprise software applications, comprising the steps of:

intercepting messages exchanged between independent services in an enterprise software application;

correlating said messages into a transaction;

determining a baseline for said enterprise software application; and

detecting deviations from said baseline.

13. The method of claim 12, said step of detecting deviations further comprising the step of:

performing an early detection of any of operation faults (bugs) in said enterprise software application and decrement in performance of said enterprise software application.

14. The method of claim 13, further comprising the step of:

detecting said operation faults during production of said enterprise software application.

15. The method of claim 12, further comprising the step of:

displaying information about any of said operation faults and performance evaluation to a user.

16. The method of claim 15, wherein said information is displayed to said user through a series of graphical user interface (GUI) views.

17. The method of claim 12, said step of intercepting messages further comprising the step of:

receiving said messages through an application programming interface (API).

18. The method of claim 12, said step of correlating said messages further comprising the steps of:

assembling messages related to an instance of a transaction;

determining an execution flow graph of a transaction instance;

mapping said execution flow graph with similar transaction instances; and

grouping said transaction instances to create an execution path that identifies said transaction.

19. The method of claim 12, wherein said baseline is determined based on any of content of said messages, context of said messages, and real-time statistics.

20. The method of claim 19, wherein said real-time statistics comprise any of:

throughput measurements, average response time measurements.

21. The method of claim 12, said method further comprising the step of:

performing a root cause analysis to detect a root cause for detected baseline deviations.

22. A computer software product readable by a machine, tangibly embodying a program of instructions executable by said machine to implement a process for detecting performance, availability, and content deviations in enterprise software applications, the method comprising the steps of:

intercepting messages exchanged between independent services of an enterprise software application;

correlating said messages into at least a business transaction;

determining a baseline for said enterprise software application; and

detecting deviations from said baseline.

23. The computer software product of claim 22, said step of detecting said deviations further comprises the step of:

performing an early detection of any of operation faults (bugs) in said enterprise software application, decrement in performance of said enterprise software application.

24. The computer software product of claim 22, further comprising the step of:

displaying information about any of operation faults and performance evaluation to a user.

25. The computer software product of claim 24, wherein said information is displayed to said user through a series of graphical user interface (GUI) views.

26. The computer software product of claim 22, said step of correlating said messages further comprising the steps of:

assembling messages related to an instance of a transaction;

determining an execution flow graph of a transaction instance;

mapping said execution flow graph with similar transaction instances; and

grouping said transaction instances to create an execution path that identifies said transaction.

27. The computer software product of claim 22, wherein said baseline is determined based on any of content of said messages, context of said messages, and real-time statistics.

28. The computer software product of claim 27, wherein said real-time statistics comprise:

throughput measurements, and average response time measurements.

29. The computer software product of claim 22, said method further comprising the step of:

performing a root cause analysis to detect a root cause for detected baseline deviations.